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Recent developments in electronic, nuclear, and defense applications have resulted in new challenges and opportunities for refractory metals and ceramics with excellent corrosion resistance and high-temperature performance. There are also effective additives for alloy and composite systems to improve their functional and structural properties in corrosive or elevated temperature environments. However, common drawbacks like room temperature brittleness and low fracture toughness prevent the use of refractory materials in applications that need high mechanical reliability. Here, Ren et al discuss the experimental and theoretical advancements in refractory materials.

Magnesium (Mg) is one of the promising metal fuels used in various applications such as flares, propellants, and rocket motor igniters. In particular, Mg is often used in the form of compounds or mixtures rather than being used alone. However, Mg is vulnerable to moisture, requiring an extra care in storage. Magnesium–Teflon–Viton (MTV), one of Mg-based mixtures, is expected to lose its combustion performance when exposed to moisture. The relative humidity (RH) conditions gave rise to the formation of an oxide film composed of magnesium oxide (MgO) and magnesium hydroxide (Mg(OH) 2 ), while Mg(OH) 2 was decomposed into MgO during the melting of polytetrafluoroethylene (Teflon). The dry conditions resulted in the formation of an oxide film composed only of MgO, which did not affect the melting of Teflon as in the RH condition. Moreover, a high-temperature environment intended for accelerated aging disrupted both pre-ignition and subsequent thermal reaction of MTV. Thus, the present work identified the changes in the thermochemical characteristics of MTV and clarified the roles of heat and moisture during such hygrothermal aging.

In order to reveal the non-uniform distribution of grain size in thick direction for engineering heavy plate, microstructure of 40 mm-thick Q345 steel was observed and measured under different short-term high temperature environments formed by fire. Moreover, the influence of the short-term high temperature environment was revealed on the distribution of ferrite grain size in the Q345 steel. Under different fire service environments, there was a log-normal distribution relationship between the distribution parameter Nf (number of ferrite grains) and df (average grain diameter), as well as ρAf (area fraction density) and df, at different positions along the thickness direction. However, the statistical results are greatly affected by the length of the statistical interval. When df is about 4 to 6 times the length of the statistical interval, the statistical accuracy is higher. By using nonlinear fitting method, multiple non-uniform distribution empirical models including Nf-df empirical formulas and ρAf-df empirical formulas were established at different positions along thick direction under various fire environments. Furthermore, the interrelationships between fire temperature T and Nf , T and ρAf , fire duration t and Nf , t and ρAf were revealed, respectively.

Human core and skin temperature (Tcr and Tsk) are crucial indicators of human health and are commonly utilized in diagnosing various types of diseases. This study presents a deep learning model that combines a long-term series forecasting method with transfer learning techniques, capable of making precise, personalized predictions of Tcr and Tsk in high-temperature environments with only a small corpus of actual training data. To practically validate the model, field experiments were conducted in complex environments, and a thorough analysis of the effects of three diverse training strategies on the overall performance of the model was performed. The comparative analysis revealed that the optimized training method significantly improved prediction accuracy for forecasts extending up to 10 min into the future. Specifically, the approach of pretraining the model on in-distribution samples followed by fine-tuning markedly outperformed other methods in terms of prediction accuracy, with a prediction error for Tcr within ±0.14 °C and Tsk, mean within ±0.46 °C. This study provides a viable approach for the precise, real-time prediction of Tcr and Tsk, offering substantial support for advancing early warning research of human thermal health.

Free vibration, damping and three-dimensional thermal buckling studies of the doubly curved sandwich viscoelastic-functionally graded (FG) material shell panels have been carried out under the high-temperature environments when subjected to uniaxial and biaxial uniform in-plane compressive loading. The sandwich-curved panels used in this analysis comprised of three layers. Base layer of the sandwich is made of aluminum, core layer of soft and thick viscoelastic material and the constraining top skin of FGM having the ceramic–metal (ZrO 2 /Ti-6Al-4 V) constituents, to incorporate the constrained layer damping (CLD) in the shell structure. The governing equation of motion has been derived through the Hamilton’s principle along with the finite element method (FEM). The influence of thermal environment or temperature gradient is considered to be imposed on the FGM top layer only, with uniform temperature distribution across the top surface of the layer. Unique temperature-dependent material constants have been considered to determine the influence of high-temperature environments on the three-dimensional thermal buckling response of the sandwich panel. The influence of various system parameters specifically top surface temperature, aspect ratio, shell geometries, core thickness ratio and power law index on the structure’s modal natural frequencies and modal loss factors has been investigated through parametric analyses. Thermal buckling and buckling response of the curved panels with respect to the parametric variations have also been presented subjected to the uniaxial and biaxial loadings. The contribution of FGM constraining skin is found presiding in many aspects toward strengthening the thermal buckling resistance of the curved sandwich panels.

Degradation of fast response pressure-sensitive paints (PSP) above room temperature is a serious problem for PSP measurements in high-temperature environments. A standard polymer-ceramic PSP (PC-PSP) composed of platinum(II)-5,10,15,20-tetrakis-(2,3,4,5,6-pentafluorphenyl)-porphyrin (PtTFPP), titania particles and poly(isobutyl methacrylate) (polyIBM) was characterized to elucidate the degradation mechanism. Applying a two-gate lifetime-based method, the PC-PSP has sufficient pressure and temperature sensitivities even at 100 °C, while the luminescence intensity significantly decreases during the test. Subsequent measurements on thermal and photostability as well as luminescence spectra reveal that the main cause of the degradation is the photodegradation of PtTFPP due to direct exposure of the dye molecules to the atmosphere. In order to suppress such degradation, a small amount of urethane resin is added to the dye solution as a simple additional step in the preparation of PC-PSP. The addition of the urethane resin significantly reduces the degradation of the PSP, although its time response is slightly slower than that of the standard PC-PSP.

The application of thermal management systems using liquid metal has been explored for aircraft converters and insulated-gate bipolar transistors of hybrid electric vehicles. Galinstan, a novel coolant used in thermal management systems, exhibits high thermal conductivity, low Prandtl number, and high boiling point, which enables its application in high-temperature environments of single-phase systems. In this study, we analyzed the heat transfer performance of Galinstan flowing through an immersion heater using computational fluid dynamics. The calculation was performed under different conditions with varying numbers of baffles, mass flow rates, and values of constant heat flux. The results provided the temperature, pressure drop, turbulence intensity, and streamlining of Galinstan. Based on the comparison of the heat transfer performance at different flow conditions, we determined the most suitable flow conditions and optimal heater design for maximizing the heat transfer performance.

Hot working environment not only affects work efficiency, but also poses a potential threat to the physical and mental health of staff. The current common method for dealing with high temperatures is spray-only or ventilation-only. To investigate the impact of different spray and ventilation modes on indoor high-temperature environments, this study examined their effects on indoor environmental parameters, average skin temperature, and psychological indicators. By establishing an experimental platform for high-temperature thermal environments, a spray ventilation cooling system was implemented, and its cooling efficacy in the indoor thermal environment was analyzed. The environmental classification of the high-temperature working environment under experimental conditions is provided based on the experimental data. A comparison and analysis of environmental parameters and physiological and psychological indicators between moderate and high-temperature environments were conducted. The combination of spray and ventilation modes resulted in a 5.3 °C reduction in air temperature, a 24.1% increase in average relative humidity, and a 3.3 °C reduction in average Wet-bulb Globe Temperature (WBGT). The cooling effect was increased by 2.3 °C and the average relative humidity was increased by 10.8% compared to spray-only and ventilation-only modes. In spray and ventilation mode, when the spray volume is increased by 15 mL/min, the air temperature is reduced by 8.2 °C, the average relative humidity is increased by 31.9%, and the average WBGT is reduced by 5.1 °C. This study has guiding significance for finding a reasonable cooling scheme to cope with indoor high-temperature environments.

Skin-like sensors capable of detecting multiple stimuli simultaneously have great potential in cutting-edge human-machine interaction. However, realizing multimodal tactile recognition beyond human tactile perception still faces significant challenges. Here, an extreme environments-adaptive multimodal triboelectric sensor was developed, capable of detecting pressure/temperatures beyond the range of human perception. Based on triboelectric nanogenerator technology, an asymmetric structure capable of independently outputting dual signals was designed to improve perception sensitivity. By converting the signals and the stimuli into feature matrices, parallel perception of complex objects (with a recognition rate of 94%) and temperature at high temperatures was achieved. The proposed multimodal triboelectric tactile sensor represents progress in maximum detection range and rapid response, realizing the upper limit of human skin’s high-temperature sensing (60 °C) with a working temperature of 200 °C. The proposed self-powered multimodal sensing system offers a wider range of possibilities for human/robot/environment interaction applications. Existing tactile sensors struggle with high-temperature environments. Here, authors developed a triboelectric tactile sensor with an asymmetric structure and heat-resistant materials, enabling 94% object recognition rate, fast response times, and stable performance up to 200 °C.

Carbon Fiber Reinforced Thermoplastics (CFRTP) are expected to be used in the automobile parts. Since the automobile parts can be subjected to the temperature up to 120 °C, the mechanical properties of CFRTP under high temperature environment should be evaluated. Although Polynonamethyleneterephthalaamide (PA9T) is an expected candidate as the highly heat resistant resin to be used for the matrix of CFRTP, the mechanical properties of CFRTP using PA9T under high temperature have not been clarified yet. In this study, the effects of molding conditions on the mechanical properties of CFRTP using PA9T were evaluated and its tensile strength under high temperature environment was measured.